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Meta-Analysis of Estimates of Life Cycle Greenhouse Gas Emissions from Concentrating Solar Power

A life cycle assessment (LCA) is a method of predicting environmental impacts of renewable energy technologies. The advantage of renewable energy plants is that they do not emit significant amounts of greenhouse gases (GHGs); however, over their lifespan they do impact the environment with GHG emissions. One such renewable energy source is concentrating solar power (CSP). Analysts have conducted LCAs of the three main CSP technologies: parabolic trough (trough), power tower (tower), and parabolic dish (dish). The current LCAs in regard to CSP technology have relatively high variability caused by a range of factors that include, “the type of technology being investigated, scope of analysis, assumed performance characteristics, location, data source, and the impact assessment methodology used” (Heath and Burkhardt 2011). Gavin A. Heath and John J. Burkhardt from the National Renewable Energy laboratory aimed to conduct a meta-analysis which reduced the variability in CSP LCAs through a method called harmonization. Harmonization takes several already published reports and aims at establishing more consistent methods and assumptions between them. As part of the larger LCA Harmonization Project of the United States’ National Renewable Energy Laboratory, this meta-analysis will be used clarify estimates of central tendency and inform future decision making in regard to CSP technology as a whole, though the estimates for specific plants will vary due to their deviation from these generic estimates.—Donald Hamnett

The three major LC phases for typical CSP plants used in the study are upstream, operational, and downstream. Upstream processes include extraction of raw materials, materials manufacturing, component manufacturing, site improvements, and plant assembly. Operational processes include manufacture and transportation of replacement components, fuel consumption in maintenance/cleaning vehicles, on-site natural gas combustion, and electricity consumption from the regional power grid. Downstream processes include plant disassembly and disposal or recycling of plant materials. In searching the English literature of environmental impacts of CSP, Heath and Burkhardt found 125 references, 13 of which provided sufficient numerical analyses yielding 42 GHG estimates (19 trough, 17 tower, 6 dish). This was trimmed to 36 for the first-level harmonization process because of how few dish estimates were given. The second level harmonization process, requiring more complete input and assumption documentation, used five trough studies with five estimates. The first “light” level of harmonization, at a gross level, adjusts emissions estimates proportionally by comparing them to consistent values for performance characteristics, creating a common system boundary. The parameters chosen for this level are solar fraction, direct normal irradiance, lifetime, solar-to-electric efficiency, global warming potentials, auxiliary natural gas consumption, and auxiliary electrical consumption. The input-intensive harmonization method used GWIs, measures of the mass of GHGs emitted from the production of common materials and from other activities.

In the light analysis, the most effective harmonization parameter was solar fraction, independently reducing the interquartile range (IQR) for trough CSP emissions by 85%. The factor that had the biggest impact on central tendency was auxiliary electrical consumption, independently increasing the median of trough emissions by 50%. Cumulatively, the light harmonization parameters decreased the trough IRQ by 69% and increased the median by 76%. For tower systems, the IQR and median were reduced by 26% and 34%, respectively. The more intensive GWI harmonization for the five trough CSP estimates assessed further reduced the median by an additional 6% and increased the range by 5%. When pooled with the 14 trough estimates not assessed in the GWI analysis, the IQR decreased by an additional 9%. These data and GHG emission estimates for CSP technology provide decision makers with a more thorough and complete view on the factors involved in the integration of this technology.